检索结果-南通市图书馆

Four decades of full-scale nitrous oxide emission inventory in China

National science Review 2024年第3期11卷 137-149页

作者： Minqi Liang Zheyan Zhou Peiyang Ren Han Xiao Xu-Ri Zhongmin Hu Shilong Piao Hanqin Tian Qing Tong Feng Zhou Jing Wei Wenping Yuan School of Atmospheric sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University State Key Laboratory of Tibetan Plateau earth system Resources and Environment Institute of Tibetan Plateau Research Chinese Academy of Sciences Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province Hainan University Sino-French institute for earth system science College of Urban and Environmental SciencesPeking University Schiller institute for Integrated science and Society Department of Earth and Environmental Sciences Boston College institute of Energy Environment and Economy Tsinghua University Southern Marine science and engineering Guangdong Laboratory(Zhuhai)

China is among the top nitrous oxide（N2O）-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade（1980–2020） of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4（1774.8–2799.9） Gg N2O yr-1in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry,energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020,respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture,industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3（290.3–344.1） Gg N2O yr-1in 1980 to 376.2（335.5–407.2） Gg N2O yr-1in 2020. Our study produces a Full-scale Annual N2O dataset in China（FAN2020）, providing emergent counting to refine the current national N2O inventories.

关键词： nitrous oxide four decades anthropogenic sources natural sources

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

MEIC-global-CO_(2):A new global CO_(2)emission inventory with highly-resolved source category and sub-country information

引用

science China earth sciences 2024年第2期67卷 450-465页

作者： Ruochong XU Dan TONG Qingyang XIAO Xinying QIN Cuihong CHEN Liu YAN Jing CHENG Can CUI Hanwen HU Wenyu LIU Xizhe YAN Huaxuan WANG Xiaodong LIU Guannan GENG Yu LEI Dabo GUAN Kebin HE Qiang ZHANG Department of earth system science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing100084China State Key joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Chinese Academy of Environmental Planning Beijing100041China institute for Carbon Neutrality Tsinghua UniversityBeijing100084China

CO_(2)emission inventory provides fundamental data for climate research and emission mitigation.Currently,most global CO_(2)emission inventories were developed with energy statistics from International Energy Agency(IEA)and were available at country level with limited source categories.Here,as the first step toward a high-resolution and dynamic updated global CO_(2)emission database,we developed a data-driven approach to construct seamless and highly-resolved energy consumption data cubes for 208 countries/territories,797 sub-country administrative divisions in 29 countries,42 fuel types,and 52 sectors,with the fusion of activity data from 24 international statistics and 65 regional/local statistics.Global CO_(2)emissions from fossil fuel combustion and cement production in 1970–2021 were then estimated with highly-resolved source category(1,484 of total)and sub-country information(797 of total).Specifically,73%of global CO_(2)emissions in 2021 were estimated with sub-country information,providing considerably improved spatial resolution for global CO_(2)emission accounting.With the support of detailed information,the dynamics of global CO_(2)emissions across sectors and fuel types were presented,representing the evolution of global economy and progress of climate mitigation.Remarkable differences of sectoral contribution were found across sub-country administrative divisions within a given country,revealing the uneven distribution of energy and economic structure among different regions.Our estimates were generally consistent with existing databases at aggregated level for global total or large emitters,while large discrepancies were observed for middle and small emitters.Our database,named the Multiresolution Emission Inventory model for Climate and air pollution research(MEIC)is publicly available through http://*** with highly-resolved information and timely update,which provides an independent carbon emission accounting data source for climate research.

关键词： CO_(2)emissions Data-driven approach Highly-resolved source category Sub-country information

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Does the continuous wetting of the Tibetan Plateau contribute to the accelerated degradation of permafrost?

引用

science China earth sciences 2024年第5期67卷 1714-1718页

作者： Yuyang WANG Jinzhi DING Shilong PIAO Sino-French institute for earth system science College of Urban and Environmental SciencesPeking UniversityBeijing 100871China State Key Laboratory of Tibetan Plateau earth system Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China

Global warming is causing the Tibetan permafrost to degrade, as evidenced by rising ground temperatures, thicker active layer thickness, thinner permafrost layer, and melting underground ice, etc.(Ran et al., 2018;Wang et al., 2020).The degradation of permafrost not only profoundly alters the carbon cycling processes in high-altitude ecosystems,thereby influencing the regional climate system, but also affects landscape hydrological connectivity。

关键词： Tibetan landscape altitude

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Oxidized organic molecules in the tropical free troposphere over Amazonia

引用

National science Review 2024年第1期11卷 174-184页

作者： Qiaozhi Zha Diego Aliaga Radovan Krejci Victoria A.Sinclair Cheng Wu Giancarlo Ciarelli Wiebke Scholz Liine Heikkinen Eva Partoll Yvette Gramlich Wei Huang Markus Leiminger Joonas Enroth Otso Per?kyl? Runlong Cai Xuemeng Chen Alkuin Maximilian Koenig Fernando Velarde Isabel Moreno Tuukka Pet?j? Paulo Artaxo Paolo Laj Armin Hansel Samara Carbone Markku Kulmala Marcos Andrade Douglas Worsnop Claudia Mohr Federico Bianchi Agrarian sciences institute Federal University of Uberl?ndia Beijing Advanced Innovation Center for Soft Matter science and engineering Beijing University of Chemical Technology Department of Atmospheric and Oceanic sciences University of Maryland Aerodyne Research Inc. Department of Environmental system science ETH Zürich Switzerland and Laboratory of Atmospheric Chemistry Paul Scherrer Institute institute for Atmospheric and earth system Research/Physics University of Helsinki joint International Research Laboratory of Atmospheric and earth system sciences Nanjing University Department of Environmental science & Bolin Centre for Climate Research Stockholm University Department of Chemistry and Molecular Biology University of Gothenburg institute for Ion and Applied Physics University of Innsbruck Ionicon Analytik GmbH Laboratory for Atmospheric Physics Institute for Physics Research Universidad Mayor de San Andrés institute of Physics University of Sao Paulo institute for Geosciences and Environmental Research (IGE) University of Grenoble Alpes

New particle formation(NPF) in the tropical free troposphere(FT) is a globally important source of cloud condensation nuclei, affecting cloud properties and climate. Oxidized organic molecules(OOMs)produced from biogenic volatile organic compounds are believed to contribute to aerosol formation in the tropical FT, but without direct chemical observations. We performed in situ molecular-level OOMs measurements at the Bolivian station Chacaltaya at 5240 m above sea level, on the western edge of Amazonia. For the first time, we demonstrate the presence of OOMs, mainly with 4–5 carbon atoms, in both gas-phase and particle-phase(in terms of mass contribution) measurements in tropical FT air from Amazonia. These observations, combined with air mass history analyses, indicate that the observed OOMs are linked to isoprene emitted from the rainforests hundreds of kilometers away. Based on particle-phase measurements, we find that these compounds can contribute to NPF, at least the growth of newly formed nanoparticles, in the tropical FT on a continental scale. Thus, our study is a fundamental and significant step in understanding the aerosol formation process in the tropical FT.

关键词： oxidized organic molecules tropical aerosol formation Amazon free troposphere

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Mixing states and secondary formation processes of organic nitrogen-containing single particles in Guangzhou,China

引用

Journal of Environmental sciences 2024年第4期138卷 62-73页

作者： Lijun Yun Chunlei Cheng Suxia Yang Zaihua Wang Mei Li Qi En Zhong LiyuanMao Sulin Liu Xiaoya Cheng Duanying Chen Fan Yang Zhen Zhou institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollutionJinan UniversityGuangzhou 510632China Guangdong-Hongkong-Macao joint Laboratory of Collaborative Innovation for Environmental Quality Guangzhou 510632China State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy ScienceXi’an 710061China institute for Environment and Climate Research Jinan UniversityGuangzhou 510632China Guangdong Academy of sciences Institute of Resources Utilization and Rare Earth DevelopmentGuangzhou 510650China Environmental Monitoring Station of Pudong New District Shanghai 201200China

Organic nitrogen(ON)compounds play a significant role in the light absorption of brown carbon and the formation of organic aerosols,however,the mixing state,secondary formation processes,and influencing factors of ON compounds are still unclear.This paper reports on the mixing state of ON-containing particles based on measurements obtained using a highperformance single particle aerosol mass spectrometer in January 2020 in Guangzhou.The ON-containing particles accounted for 21% of the total detected single particles,and the particle count and number fraction of the ON-containing particles were two times higher at night than during the day.The prominent increase in the content of ON-containing particles with the enhancement of NO_xmainly occurred at night,and accompanied by high relative humidity and nitrate,which were associated with heterogeneous reactions between organics and gaseous NO_(x)and/or NO_(3)radical.The synchronous decreases in ON-containing particles and the mass absorption coefficient of water-soluble extracts at 365 nm in the afternoon may be associated with photo-bleaching of the ON species in the particles.In addition,the positive matrix factorization analysis found five factors dominated the formation processes of ON particles,and the nitrate factor(33%)mainly contributed to the production of ON particles at night.The results of this study provide unique insights into the mixing states and secondary formation processes of the ON-containing particles.

关键词： Organic nitrogen compounds Single particles Mixing state Secondary formation Nighttime chemistry

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Community-Level Practice Checklists for Health Protection During Cold Spells in China

引用

China CDC weekly 2024年第5期6卷 83-87页

作者： Jing Shang Mengzhen Zhao Zhao Liu Xiya Zhang Shiguang Miao Ishaq D.Sulaymon Wenjia Cai institute of Urban Meteorology CMABeijingChina School of Management and Economics Beijing Institute of TechnologyBeijingChina School of Airport Economics and Management Beijing Institute of Economics and ManagementBeijingChina Department of earth system science Tsinghua UniversityBeijingChina Sand and Dust Storm Warning regional Center National Center for MeteorologyJeddahSaudi Arabia Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing CityJiangsu ProvinceChina

Communities play a crucial role in protecting the health of vulnerable populations such as the elderly,low-income groups,and high-risk individuals during cold spells.However,current strategies for responding to cold spells primarily consist of programmatic policies that lack practicality,specificity,and detailed implementation guidelines for community workers.Therefore,this study aims to identify and analyze the challenges faced by communities in responding to cold spells,review international experiences,and develop a set of practical checklists for community-level health protection.These checklists will assist community workers and volunteers in effectively preparing for,responding to,and recovering from cold spells.

关键词： preparing income primarily

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

引用

Advances in Atmospheric sciences 2024年第7期41卷 1326-1341页

作者： Lu LI Yongjiu DAI Zhongwang WEI Wei SHANGGUAN Nan WEI Yonggen ZHANG Qingliang LI Xian-Xiang LI School of Atmospheric sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine science and engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Guangzhou 510275China institute of Surface-earth system science School of Earth System ScienceTianjin UniversityTianjin 300072China College of Computer science and Technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast system to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Carbon uptake by cement in China:Estimation and contribution to carbon neutrality goals

引用

science China earth sciences 2024年第6期67卷 2056-2067页

作者： Mingjing MA Zi HUANG Jiaoyue WANG Le NIU Wenfeng ZHANG Xiaowei XU Fengming XI Zhu LIU institute of Applied Ecology Chinese Academy of SciencesShenyang 110016China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China Department of earth system science Tsinghua UniversityBeijing 100084China Department of engineering science University of OxfordOxfordOX13UK

Cement is a widely used construction material globally.Its manufacturing contributes to anthropogenic CO_(2)emissions significantly.However,its alkaline compounds can absorb CO_(2)from the surrounding environment and engage in a carbonation reaction,thereby functioning as a carbon sink.As a major cement producer and consumer,China has an important responsibility to rigorously investigate and accurately account for cement carbon uptake.This study presents a comprehensive analytical model of cement carbon uptake from China,revealing a substantial increase in carbon uptake from 1930 to 2021,peaking at 426.77 Mt CO_(2)(95% Confidence Interval:317.67-874.33 Mt CO_(2))in 2021.The uptake accounts for 8.10% to 45.40% of China’s annual land sink and 2.51% to 4.54% of the global land sink.The cumulative carbon uptake by cement is approximately 7.06 Gt CO_(2)(95%CI:5.22–9.44 Gt CO_(2))during this period,offsetting 50.7% of the total emissions(13.91 Gt CO_(2),95%CI:12.44–17.00 Gt CO_(2))from the cement industry.Notably,cement mortar contributed to most absorption(65.64%).From a life cycle perspective,the service stage of cement materials is the period where the largest CO_(2)sink is formed,accounting for 90.03% of the total.Therefore,the potential for carbon sequestration in cement materials and their waste is enormous.Additionally,the model improves the accuracy of cement carbon accounting,supporting both China and global carbon neutrality assessments.Thus,it is crucial for China to achieve its carbon neutrality goals sooner by prioritizing the environmental benefits of cement materials and wastes,and accelerating the development and commercialization of CO_(2)sequestration technologies for cement and its by-products.

关键词： Cement Carbon uptake Life cycle assessment Carbon emission reduction Carbon neutrality

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

引用

Advances in Atmospheric sciences 2024年第7期41卷 1299-1312页

作者： Ya WANG Gang HUANG Baoxiang PAN Pengfei LIN Niklas BOERS Weichen TAO Yutong CHEN BO LIU Haijie LI State Key Laboratory of Numerical Modeling for Atmospheric sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of earth and Planetary sciences University of Chinese Academy of SciencesBeijing 100049China earth system Modelling School of Engineering and DesignTechnical University of MunichOttobrunn 85521Germany Potsdam institute for Climate Impact Research Potsdam 14412Germany Department of Mathematics and Global systems institute University of ExeterExeter EX44QEUK CMA earth system Modeling and Prediction Centre(CEMC) Chinese Academy of Meteorological SciencesBeijing 100081China

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community earth system Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

关键词： generative adversarial networks model bias deep learning El Niño-Southern Oscillation marine heatwaves

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

引用

Advances in Atmospheric sciences 2024年第6期41卷 1083-1099,I0002,I0003页

作者： Yang XIA Bin WANG Lijuan LI Li LIU Jianghao LI Li DONG Shiming XU Yiyuan LI Wenwen XIA Wenyu HUANG Juanjuan LIU Yong WANG Hongbo LIU Ye PU Yujun HE Kun XIA Ministry of Education Key Laboratory for earth system Modeling and Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Laboratory of Numerical Modeling for Atmospheric sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Innovation Group 311020008 Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519000China Shanghai Ecological Forecasting and Remote Sensing Center Shanghai 200030China Key Laboratory of earth system Modeling and Prediction China Meteorological AdministrationBeijing 100081China College of Ocean sciences University of Chinese Academy of SciencesBeijing 100049China

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

关键词： neural network nonhydrostatic alternative scheme atmospheric model dynamical core

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：